import pymysql
import pandas as pd


class MysqlUtils(object):
    def __init__(self):
        self.conn = pymysql.connect(
            host='127.0.0.1',
            user="root",
            passwd="root",
            db="tushare1",
            port=3306,
            charset="utf8"
        )
        
class classIfication(object):
    
    # 获取财务表相关数据
    def get_fina_indicator(self, conn):
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        
        sql = """SELECT ts_code, ann_date, eps, total_revenue_ps, undist_profit_ps, 
        gross_margin, fcff, fcfe, tangible_asset, bps, grossprofit_margin, npta, roic 
        FROM financial_data WHERE ann_date >= '2023-01-01' and ann_date<'2024-01-01'"""
        
        cursor.execute(sql)
        ret = cursor.fetchall()
        # print(ret)
        df = pd.DataFrame(ret)
        df1 = df.dropna(subset=['eps', 'total_revenue_ps', 'undist_profit_ps', 
                                'gross_margin', 'fcff', 'fcfe', 'tangible_asset',
                                'bps', 'grossprofit_margin', 'npta', 'roic'])
        # 重建索引
        df1 = df1.reset_index(drop=False)
        print(df1.head)
        
        return df1
        
        
    # 获取日线行情
    def get_daily(self, conn, df1):
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        new_list = []
        
        for i in range(len(df1['ts_code'])):
            try:
                print(i)
                ann_date_str = df1['ann_date'][i].strftime('%Y%m%d')
                sql = 'select trade_date, closes, opens, high, low from date_1 where ts_code = \'' \
                    + df1['ts_code'][i] + '\' and trade_date > Date(\''+ ann_date_str \
                        +'\') order by trade_date limit 20'
                cursor.execute(sql)
                ret = cursor.fetchall()
                
                df2 = pd.DataFrame(ret)
                if len(df2) > 0:
                    max_close = df2['closes'].max()
                    min_close = df2['closes'].min()
                    the_close = df2['closes'].iloc[1]
                    new_list.append({
                        'ts_code': df1['ts_code'][i],
                        'ann_date': df1['ann_date'][i],
                        'max_close': max_close,
                        'min_close': min_close,
                        'the_close': the_close,
                        'eps': df1['eps'][i],
                        'total_revenue_ps': df1['total_revenue_ps'][i],
                        'undist_profit_ps': df1['undist_profit_ps'][i],
                        'gross_margin': df1['gross_margin'][i],
                        'fcff': df1['fcff'][i],
                        'fcfe': df1['fcfe'][i],
                        'tangible_asset': df1['tangible_asset'][i],
                        'bps': df1['bps'][i],
                        'grossprofit_margin': df1['grossprofit_margin'][i],
                        'npta': df1['npta'][i],
                        'roic': df1['roic'][i],
                    })
            except Exception as e:
                print(e)
        df3 = pd.DataFrame(new_list)
        df3.to_csv('daily.csv', index=False)

            
if __name__ == '__main__':
    mu = MysqlUtils()
    ci = classIfication()
    df = ci.get_fina_indicator(mu.conn)
    ci.get_daily(mu.conn, df)
    